Mechanisms of cellular mRNA transcript homeostasis

Global control of RNA polymerase II

RNA polymerase II (Pol II) is the multi-protein complex responsible for transcribing all protein-coding messenger RNA (mRNA). Most research on gene regulation is focused on the mechanisms controlling which genes are transcribed when, or on the mechanics of transcription. How global Pol II activity is determined receives comparatively less attention. Here, we follow the life of a Pol II molecule from 'assembly of the complex' to nuclear import, enzymatic activity, and degradation. We focus on how Pol II spends its time in the nucleus, and on the two-way relationship between Pol II abundance and activity in the context of homeostasis and global transcriptional changes.

Information Transmission through Biotic-Abiotic Interfaces to Restore or Enhance Human Function

Advancements in reliable information transfer across biotic-abiotic interfaces have enabled the restoration of lost human function. For example, communication between neuronal cells and electrical devices restores the ability to walk to a tetraplegic patient and vision to patients blinded by retinal disease. These impactful medical achievements are aided by tailored biotic-abiotic interfaces that maximize information transfer fidelity by considering the physical properties of the underlying biological and synthetic components. This Review develops a modular framework to define and describe the engineering of biotic and abiotic components as well as the design of interfaces to facilitate biotic-abiotic information transfer using light or electricity. Delineating the properties of the biotic, interface, and abiotic components that enable communication can serve as a guide for future research in this highly interdisciplinary field. Application of synthetic biology to engineer light-sensitive proteins has facilitated the control of neural signaling and the restoration of rudimentary vision after retinal blindness. Electrophysiological methodologies that use brain-computer interfaces and stimulating implants to bypass spinal column injuries have led to the rehabilitation of limb movement and walking ability. Cellular interfacing methodologies and on-chip learning capability have been made possible by organic transistors that mimic the information processing capacity of neurons. The collaboration of molecular biologists, material scientists, and electrical engineers in the emerging field of biotic-abiotic interfacing will lead to the development of prosthetics capable of responding to thought and experiencing touch sensation via direct integration into the human nervous system. Further interdisciplinary research will improve electrical and optical interfacing technologies for the restoration of vision, offering greater visual acuity and potentially color vision in the near future.

Gene-specific RNA homeostasis revealed by perturbation of coactivator complexes

Transcript buffering entails the reciprocal modulation of mRNA synthesis and degradation rates to maintain stable RNA levels under varying cellular conditions. Current research supports a global, non-sequence-specific connection between mRNA synthesis and degradation, but the underlying mechanisms are still unclear. In this study, we investigated changes in RNA metabolism following acute depletion of TIP60/KAT5, the acetyltransferase subunit of the NuA4 transcriptional coactivator complex, in mouse embryonic stem cells. By combining RNA sequencing of nuclear, cytoplasmic, and newly synthesised transcript fractions with biophysical modelling, we demonstrate that TIP60 predominantly enhances transcription of numerous genes, while a smaller set of genes undergoes TIP60-dependent transcriptional repression. Surprisingly, transcription changes caused by TIP60 depletion were offset by corresponding changes in RNA nuclear export and cytoplasmic stability, indicating gene-specific buffering mechanisms. Similarly, disruption of the unrelated ATAC coactivator complex also resulted in gene-specific transcript buffering. These findings reveal that transcript buffering functions at a gene-specific level and suggest that cells dynamically adjust RNA splicing, export, and degradation in response to individual RNA synthesis alterations, thereby sustaining cellular homeostasis.

Nuclear RNA homeostasis promotes systems-level coordination of cell fate and senescence

Understanding cellular coordination remains a challenge despite knowledge of individual pathways. The RNA exosome, targeting a wide range of RNA substrates, is often downregulated in cellular senescence. Utilizing an auxin-inducible system, we observed that RNA exosome depletion in embryonic stem cells significantly affects the transcriptome and proteome, causing pluripotency loss and pre-senescence onset. Mechanistically, exosome depletion triggers acute nuclear RNA aggregation, disrupting nuclear RNA-protein equilibrium. This disturbance limits nuclear protein availability and hinders polymerase initiation and engagement, reducing gene transcription. Concurrently, it promptly disrupts nucleolar transcription, ribosomal processes, and nuclear exporting, resulting in a translational shutdown. Prolonged exosome depletion induces nuclear structural changes resembling senescent cells, including aberrant chromatin compaction, chromocenter disassembly, and intensified heterochromatic foci. These effects suggest that the dynamic turnover of nuclear RNA orchestrates crosstalk between essential processes to optimize cellular function. Disruptions in nuclear RNA homeostasis result in systemic functional decline, altering the cell state and promoting senescence.

Influence of cell volume on the gene transcription rate

Cells vary in volume throughout their life cycle and in many other circumstances, while their genome remains identical. Hence, the RNA production factory must adapt to changing needs, while maintaining the same production lines. This paradox is resolved by different mechanisms in distinct cells and circumstances. RNA polymerases have evolved to cope with the particular circumstances of each case and the different characteristics of the several RNA molecule types, especially their stabilities. Here we review current knowledge on these issues. We focus on the yeast Saccharomyces cerevisiae, where many of the studies have been performed, although we compare and discuss the results obtained in other eukaryotes and propose several ideas and questions to be tested and solved in the future. TAKE AWAY.

Subscaling of a cytosolic RNA binding protein governs cell size homeostasis in the multiple fission alga Chlamydomonas

Coordination of growth and division in eukaryotic cells is essential for populations of proliferating cells to maintain size homeostasis, but the underlying mechanisms that govern cell size have only been investigated in a few taxa. The green alga Chlamydomonas reinhardtii (Chlamydomonas) proliferates using a multiple fission cell cycle that involves a long G1 phase followed by a rapid series of successive S and M phases (S/M) that produces 2n daughter cells. Two control points show cell-size dependence: the Commitment control point in mid-G1 phase requires the attainment of a minimum size to enable at least one mitotic division during S/M, and the S/M control point where mother cell size governs cell division number (n), ensuring that daughter distributions are uniform. tny1 mutants pass Commitment at a smaller size than wild type and undergo extra divisions during S/M phase to produce small daughters, indicating that TNY1 functions to inhibit size-dependent cell cycle progression. TNY1 encodes a cytosolic hnRNP A-related RNA binding protein and is produced once per cell cycle during S/M phase where it is apportioned to daughter cells, and then remains at constant absolute abundance as cells grow, a property known as subscaling. Altering the dosage of TNY1 in heterozygous diploids or through mis-expression increased Commitment cell size and daughter cell size, indicating that TNY1 is a limiting factor for both size control points. Epistasis placed TNY1 function upstream of the retinoblastoma tumor suppressor complex (RBC) and one of its regulators, Cyclin-Dependent Kinase G1 (CDKG1). Moreover, CDKG1 protein and mRNA were found to over-accumulate in tny1 cells suggesting that CDKG1 may be a direct target of repression by TNY1. Our data expand the potential roles of subscaling proteins outside the nucleus and imply a control mechanism that ties TNY1 accumulation to pre-division mother cell size.

Coordination of rhythmic RNA synthesis and degradation orchestrates 24- and 12-h RNA expression patterns in mouse fibroblasts

Circadian RNA expression is essential to ultimately regulate a plethora of downstream rhythmic biochemical, physiological, and behavioral processes. Both transcriptional and posttranscriptional mechanisms are considered important to drive rhythmic RNA expression; however, the extent to which each regulatory process contributes to the rhythmic RNA expression remains controversial. To systematically address this, we monitored RNA dynamics using metabolic RNA labeling technology during a circadian cycle in mouse fibroblasts. We find that rhythmic RNA synthesis is the primary contributor of 24-h RNA rhythms, while rhythmic degradation is more important for 12-h RNA rhythms. These rhythms were predominantly regulated by Bmal1 and/or the core clock mechanism, and the interplay between rhythmic synthesis and degradation has a significant impact in shaping rhythmic RNA expression patterns. Interestingly, core clock RNAs are regulated by multiple rhythmic processes and have the highest amplitude of synthesis and degradation, presumably critical to sustain robust rhythmicity of cell-autonomous circadian rhythms. Our study yields invaluable insights into the temporal dynamics of both 24- and 12-h RNA rhythms in mouse fibroblasts.

New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges

Despite a standardized diagnostic examination, cancer of unknown primary (CUP) is a rare metastatic malignancy with an unidentified tissue of origin (TOO). Patients diagnosed with CUP are typically treated with empiric chemotherapy, although their prognosis is worse than those with metastatic cancer of a known origin. TOO identification of CUP has been employed in precision medicine, and subsequent site-specific therapy is clinically helpful. For example, molecular profiling, including genomic profiling, gene expression profiling, epigenetics and proteins, has facilitated TOO identification. Moreover, machine learning has improved identification accuracy, and non-invasive methods, such as liquid biopsy and image omics, are gaining momentum. However, the heterogeneity in prediction accuracy, sample requirements and technical fundamentals among the various techniques is noteworthy. Accordingly, we systematically reviewed the development and limitations of novel TOO identification methods, compared their pros and cons and assessed their potential clinical usefulness. Our study may help patients shift from empirical to customized care and improve their prognoses.

Quantifying and correcting bias in transcriptional parameter inference from single-cell data

The snapshot distribution of mRNA counts per cell can be measured using single-molecule fluorescence in situ hybridization or single-cell RNA sequencing. These distributions are often fit to the steady-state distribution of the two-state telegraph model to estimate the three transcriptional parameters for a gene of interest: mRNA synthesis rate, the switching on rate (the on state being the active transcriptional state), and the switching off rate. This model assumes no extrinsic noise, i.e., parameters do not vary between cells, and thus estimated parameters are to be understood as approximating the average values in a population. The accuracy of this approximation is currently unclear. Here, we develop a theory that explains the size and sign of estimation bias when inferring parameters from single-cell data using the standard telegraph model. We find specific bias signatures depending on the source of extrinsic noise (which parameter is most variable across cells) and the mode of transcriptional activity. If gene expression is not bursty then the population averages of all three parameters are overestimated if extrinsic noise is in the synthesis rate; underestimation occurs if extrinsic noise is in the switching on rate; both underestimation and overestimation can occur if extrinsic noise is in the switching off rate. We find that some estimated parameters tend to infinity as the size of extrinsic noise approaches a critical threshold. In contrast when gene expression is bursty, we find that in all cases the mean burst size (ratio of the synthesis rate to the switching off rate) is overestimated while the mean burst frequency (the switching on rate) is underestimated. We estimate the size of extrinsic noise from the covariance matrix of sequencing data and use this together with our theory to correct published estimates of transcriptional parameters for mammalian genes.

Split Luciferase-Fragment Reconstitution for Unveiling RNA Localization and Dynamics in Live Cells

The intracellular distribution and dynamics of RNAs play pivotal roles in various physiological phenomena. The ability to monitor the amount and localization of endogenous RNAs in living cells allows for elucidating the mechanisms of various intracellular events. Protein-based fluorescent RNA probes are now widely used to visualize and analyze RNAs in living cells. However, continuously monitoring the temporal changes in RNA localization and dynamics in living cells is challenging. In this study, we developed a bioluminescent probe for spatiotemporal monitoring of RNAs in living cells by using a split-luciferase reconstitution technique. The probe consists of split fragments of a bioluminescent protein, NanoLuc, connected with RNA-binding protein domains generated from a custom-made mutation of a PUM-HD. The probe showed rapid luminescence intensity changes in response to an increase or decrease in the amount of a target RNA in vitro. In live-cell imaging, temporal alteration of the intracellular distribution of endogenous β-actin mRNA was visualized in response to extracellular stimulation. Furthermore, the application of the probe to the visualization of the specific localization of β-actin mRNA in primary hippocampal neurons was conducted. These results demonstrate the capability of the bioluminescent RNA probe to monitor the changes in localization, dynamics, and the amount of target RNA in living cells.

Poisson representation: a bridge between discrete and continuous models of stochastic gene regulatory networks

Stochastic gene expression dynamics can be modelled either discretely or continuously. Previous studies have shown that the mRNA or protein number distributions of some simple discrete and continuous gene expression models are related by Gardiner's Poisson representation. Here, we systematically investigate the Poisson representation in complex stochastic gene regulatory networks. We show that when the gene of interest is unregulated, the discrete and continuous descriptions of stochastic gene expression are always related by the Poisson representation, no matter how complex the model is. This generalizes the results obtained in Dattani & Barahona (Dattani & Barahona 2017 J. R. Soc. Interface 14, 20160833 (doi:10.1098/rsif.2016.0833)). In addition, using a simple counter-example, we find that the Poisson representation in general fails to link the two descriptions when the gene is regulated. However, for a general stochastic gene regulatory network, we demonstrate that the discrete and continuous models are approximately related by the Poisson representation in the limit of large protein numbers. These theoretical results are further applied to analytically solve many complex gene expression models whose exact distributions are previously unknown.

Self-demixing of mRNA copies buffers mRNA:mRNA and mRNA:regulator stoichiometries

Cellular homeostasis requires the robust control of biomolecule concentrations, but how do millions of mRNAs coordinate their stoichiometries in the face of dynamic translational changes? Here, we identified a two-tiered mechanism controlling mRNA:mRNA and mRNA:protein stoichiometries where mRNAs super-assemble into condensates with buffering capacity and sorting selectivity through phase-transition mechanisms. Using C. elegans oogenesis arrest as a model, we investigated the transcriptome cytosolic reorganization through the sequencing of RNA super-assemblies coupled with single mRNA imaging. Tightly repressed mRNAs self-assembled into same-sequence nanoclusters that further co-assembled into multiphase condensates. mRNA self-sorting was concentration dependent, providing a self-buffering mechanism that is selective to sequence identity and controls mRNA:mRNA stoichiometries. The cooperative sharing of limiting translation repressors between clustered mRNAs prevented the disruption of mRNA:repressor stoichiometries in the cytosol. Robust control of mRNA:mRNA and mRNA:protein stoichiometries emerges from mRNA self-demixing and cooperative super-assembly into multiphase multiscale condensates with dynamic storage capacity.

Coordination of rhythmic RNA synthesis and degradation orchestrates 24-hour and 12-hour RNA expression patterns in mouse fibroblasts

Circadian RNA expression is essential to ultimately regulate a plethora of downstream rhythmic biochemical, physiological, and behavioral processes. Both transcriptional and post-transcriptional mechanisms are considered important to drive rhythmic RNA expression, however, the extent to which each regulatory process contributes to the rhythmic RNA expression remains controversial. To systematically address this, we monitored RNA dynamics using metabolic RNA labeling technology during a circadian cycle in mouse fibroblasts. We find that rhythmic RNA synthesis is the primary contributor of 24 hr RNA rhythms, while rhythmic degradation is more important for 12 hr RNA rhythms. These rhythms were predominantly regulated by Bmal1 and/or the core clock mechanism, and interplay between rhythmic synthesis and degradation has a significant impact in shaping rhythmic RNA expression patterns. Interestingly, core clock RNAs are regulated by multiple rhythmic processes and have the highest amplitude of synthesis and degradation, presumably critical to sustain robust rhythmicity of cell-autonomous circadian rhythms. Our study yields invaluable insights into the temporal dynamics of both 24 hr and 12 hr RNA rhythms in mouse fibroblasts.

Mechanisms regulating the properties of inhibition-based gamma oscillations in primate prefrontal and parietal cortices

In primates, the dorsolateral prefrontal (DLPFC) and posterior parietal (PPC) cortices are key nodes in the working memory network. The working memory-related gamma oscillations induced in these areas, predominantly in layer 3, exhibit higher frequency in DLPFC. Although these regional differences in oscillation frequency are likely essential for information transfer between DLPFC and PPC, the mechanisms underlying these differences remain poorly understood. We investigated, in rhesus monkey, the DLPFC and PPC layer 3 pyramidal neuron (L3PN) properties that might regulate oscillation frequency and assessed the effects of these properties simulating oscillations in computational models. We found that GABAAR-mediated synaptic inhibition synchronizes L3PNs in both areas, but analysis of GABAAR mRNA levels and inhibitory synaptic currents suggested similar mechanisms of inhibition-mediated synchrony in DLPFC and PPC. Basal dendrite spine density and AMPAR/NMDAR mRNA levels were higher in DLPFC L3PNs, whereas excitatory synaptic currents were similar between areas. Therefore, synaptically evoked excitation might be stronger in DLPFC L3PNs due to a greater quantity of synapses in basal dendrites, a main target of recurrent excitation. Simulations in computational networks showed that oscillation frequency and power increased with increasing recurrent excitation, suggesting a mechanism by which the DLPFC–PPC differences in oscillation properties are generated.

Prediction of transcript structure and concentration using RNA-Seq data

Alternative splicing (AS) is a key post-transcriptional modification that helps in increasing protein diversity. Almost 90% of the protein-coding genes in humans are known to undergo AS and code for different transcripts. Some transcripts are associated with diseases such as breast cancer, lung cancer and glioblastoma. Hence, these transcripts can serve as novel therapeutic and prognostic targets for drug discovery. Herein, we have developed a pipeline, Finding Alternative Splicing Events (FASE), as the R package that includes modules to determine the structure and concentration of transcripts using differential AS. To predict the correct structure of expressed transcripts in given conditions, FASE combines the AS events with the information of exons, introns and junctions using graph theory. The estimated concentration of predicted transcripts is reported as the relative expression in terms of log2CPM. Using FASE, we were able to identify several unique transcripts of EMILIN1 and SLK genes in the TCGA-BRCA data, which were validated using RT-PCR. The experimental study demonstrated consistent results, which signify the high accuracy and precision of the developed methods. In conclusion, the developed pipeline, FASE, can efficiently predict novel transcripts that are missed in general transcript-level differential expression analysis. It can be applied selectively from a single gene to simple or complex genome even in multiple experimental conditions for the identification of differential AS-based biomarkers, prognostic targets and novel therapeutics.

Coupling gene expression dynamics to cell size dynamics and cell cycle events: Exact and approximate solutions of the extended telegraph model

The standard model describing the fluctuations of mRNA numbers in single cells is the telegraph model which includes synthesis and degradation of mRNA, and switching of the gene between active and inactive states. While commonly used, this model does not describe how fluctuations are influenced by the cell cycle phase, cellular growth and division, and other crucial aspects of cellular biology. Here, we derive the analytical time-dependent solution of an extended telegraph model that explicitly considers the doubling of gene copy numbers upon DNA replication, dependence of the mRNA synthesis rate on cellular volume, gene dosage compensation, partitioning of molecules during cell division, cell-cycle duration variability, and cell-size control strategies. Based on the time-dependent solution, we obtain the analytical distributions of transcript numbers for lineage and population measurements in steady-state growth and also find a linear relation between the Fano factor of mRNA fluctuations and cell volume fluctuations. We show that generally the lineage and population distributions in steady-state growth cannot be accurately approximated by the steady-state solution of extrinsic noise models, i.e. a telegraph model with parameters drawn from probability distributions. This is because the mRNA lifetime is often not small enough compared to the cell cycle duration to erase the memory of division and replication. Accurate approximations are possible when this memory is weak, e.g. for genes with bursty expression and for which there is sufficient gene dosage compensation when replication occurs.

Post-Transcriptional Control of mRNA Metabolism and Protein Secretion: The Third Level of Regulation within the NF-κB System

The NF-κB system is a key transcriptional pathway that regulates innate and adaptive immunity because it triggers the activation and differentiation processes of lymphocytes and myeloid cells during immune responses. In most instances, binding to cytoplasmic inhibitory IκB proteins sequesters NF-κB into an inactive state, while a plethora of external triggers activate three complex signaling cascades that mediate the release and nuclear translocation of the NF-κB DNA-binding subunits. In addition to these cytosolic steps (level 1 of NF-κB regulation), NF-κB activity is also controlled in the nucleus by signaling events, cofactors and the chromatin environment to precisely determine chromatin recruitment and the specificity and timing of target gene transcription (level 2 of NF-κB regulation). Here, we discuss an additional layer of the NF-κB system that manifests in various steps of post-transcriptional gene expression and protein secretion. This less-studied regulatory level allows reduction of (transcriptional) noise and signal integration and endows time-shifted control of the secretion of inflammatory mediators. Detailed knowledge of these steps is important, as dysregulated post-transcriptional NF-κB signaling circuits are likely to foster chronic inflammation and contribute to the formation and maintenance of a tumor-promoting microenvironment.

Nucleo-cytoplasmic shuttling of RNA-binding factors: mRNA buffering and beyond

Gene expression is a highly regulated process that adapts RNAs and proteins content to the cellular context. Under steady-state conditions, mRNA homeostasis is robustly maintained by tight controls that act on both nuclear transcription and cytoplasmic mRNA stability. In recent years, it has been revealed that several RNA-binding proteins (RBPs) that perform functions in mRNA decay can move to the nucleus and regulate transcription. The RBPs involved in transcription can also travel to the cytoplasm and regulate mRNA degradation and/or translation. The multifaceted functions of these shuttling nucleo-cytoplasm RBPs have raised the possibility that they can act as mRNA metabolism coordinators. In addition, this indicates the existence of crosstalk mechanisms between the enzymatic machineries that drive the different mRNA life-cycle phases. The buffering of the mRNA concentration is the best known consequence of a transcription-degradation crosstalk counteraction, but alternative ways of RBP action can also imply enhanced gene regulation.